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claude-code

Claude-Code-Agent-Monitor sprint-summary

install
source · Clone the upstream repo
git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/ccam-productivity/skills/sprint-summary" ~/.claude/skills/hoangsonww-claude-code-agent-monitor-sprint-summary && rm -rf "$T"
manifest: plugins/ccam-productivity/skills/sprint-summary/SKILL.md
source content

Sprint Summary

Generate a sprint summary from Claude Code Agent Monitor data.

Input

The user provides: $ARGUMENTS

This may be:

  • A sprint duration: "last 2 weeks", "last 10 days"
  • A date range: "2025-03-31 to 2025-04-13"
  • "current sprint" (default: last 14 days)

Procedure

  1. Fetch sprint data from 

    http://localhost:4820
    :

    • GET /api/sessions?limit=500
      — all sessions in range (default sort: most recently updated first)
    • GET /api/analytics
      — aggregated metrics
    • GET /api/pricing/cost
      — total costs
    • For high-value sessions: 
      GET /api/events?session_id={id}
      — event details

  2. Compile sprint summary:

    🎯 Sprint Overview

    • Sprint period: [start] to [end]
    • Total sessions: N (completed: N, errored: N, abandoned: N)
    • Total development hours with Claude Code: N
    • Total cost: $X.XX
    • Overall completion rate: N%

    📦 Deliverables

    Group sessions by working directory (project):

    • Project A (
      /path/to/project
      )
      • N sessions, N hours, key activities
    • Project B (
      /path/to/other
      )
      • N sessions, N hours, key activities

    📊 Velocity Metrics

    MetricSprintPrevious SprintTrend
    Sessions/dayNN↑/↓
    Avg session durationNmNm↑/↓
    Cost/session$N$N↑/↓
    Tokens/sessionNN↑/↓
    Completion rateN%N%↑/↓

    🛠 Technology Breakdown

    • Models used with distribution percentages
    • Top 15 tools by usage with category grouping
    • Subagent utilization rate

    ⚡ Efficiency Analysis

    • Token efficiency: cache hit rate, compaction frequency
    • Cost per completed task
    • Time-to-first-output (avg across sessions)
    • Error recovery rate (sessions that recovered from errors)

    🔄 Retrospective Data Points

    • What went well: Highest-efficiency sessions, best completion rates
    • What could improve: Most expensive sessions, highest error rates
    • Action items: Data-driven suggestions for next sprint

Output Format

Professional sprint report suitable for sharing with team leads or managers:

  • Executive summary paragraph (5 sentences max)
  • Structured data tables with trend indicators
  • Grouped deliverables by project
  • Numbered action items at the end